For city dwellers, our ability to move easily within our cities influences our economic opportunities, our health, the people we encounter, and much more. Taken together, urban mobility patterns influence our collective future, as well. For example, changes in mobility patterns in North American cities as a result of sprawl led to increased carbon emissions, accelerated climate change, and, as a result, will continue to alter urban lifestyles across the world for decades to come. Research on urban mobility must always consider economic, social, and environmental justice and avoid simplifications that prioritize economic bottom-lines.
In this brief research proposal, I will first provide an example of how I have used mobility and economic data in the European context, which illustrates the need for individual-level data that is collected thoughtfully and with a justice lens. I will then describe the research I would like to conduct, with Addis Ababa as an initial case study. The outputs of this research would include, of course, peer-reviewed academic publications, but also toolkits and data that can be shared with local leaders and activists. I believe these latter outputs are crucial.
My previous research has focused on European cities and investigated relationships between urban geography and sociopolitical attitudes (Kent, 2022; Rodon & Kent, 2023; Kent, 2024a) and relationships between urban land use and human mobility (Kent, 2024b, 65-86). As the following example demonstrates, aggregated mobility data, like that available for Spain, reveals interesting directions for research despite certain unfortunate limitations.
Below is a partial map of flows between districts in Madrid on a typical weekday in 2019 based on data from over 40 million mobile phones collected by the National Statistics Institute of Spain. Classical models of urban mobility, like the gravity model (Zipf, 1946), assume that commuters are drawn toward centers of economic activity or other key hubs (such as hospitals or educational centers). However, the data reveals a great deal of additional complexity, even when aggregated.
One measure of mobility for a given district is the daytime population of the district vs. the nighttime population. Districts with a lower daytime population are subject to outward mobility as many of its residents spend their days seeking opportunities (economic, educational, social, etc.) elsewhere in the city. The map below includes this measure of mobility along with the median household income for each district (toggle between metrics using the layers menu).